The paper presents the study of the project on which we are working, to enhance the safety measures of the drivers. It will detect the drowsiness of the driver and will ensure their safety. As we know many drivers lose their lives every year due to tragic road accidents and the main reason behind that is the fatigue or the sleepiness of the drivers. The conventional methods that are used to detect the fatigue of the driver are the behavioural features while others need extravagant devices. For that reason, we developed a drowsiness detection system in real time. This system analyses the facial features and detects the drowsiness of the driver in real time by using an image processing technique CONVOLUTIONAL NEURAL NETWORK (CNN). In this eye aspect ratio and closure ratio is computed to detect the fatigue of the driver. PYTHON is used to test the intended approach competence.


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    Titel :

    Drowsiness Detection System in Real Time


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Suhag, Sathans (Herausgeber:in) / Mahanta, Chitralekha (Herausgeber:in) / Mishra, Sukumar (Herausgeber:in) / Kaushik, Sheersh (Autor:in) / Gupta, Purnima (Autor:in) / Singh, Vineet Kumar (Autor:in) / Maan, Sonal (Autor:in) / Faraz, Saquib (Autor:in)


    Erscheinungsdatum :

    2022-02-01


    Format / Umfang :

    8 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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